code: def _get_eval_args(
      self, output_path: str, args: EvalArgs
  ) -> TrainingArguments:
      deepspeed = self.__get_deepspeed_config(args, False)
  
      return TrainingArguments(
          output_dir=output_path,
          seed=42,
          report_to=["none"],
          per_device_eval_batch_size=args.batch_size,
          use_mps_device=True if self.device.type == "mps" else False,
          deepspeed=deepspeed,
      )
  
imports: import logging
  import os
  import tempfile
  from typing import Union
  from datasets import Dataset, DatasetDict, load_dataset, load_from_disk
  import torch
  from transformers import AutoConfig, AutoModel, AutoTokenizer, Seq2SeqTrainer, Seq2SeqTrainingArguments, Trainer, TrainingArguments
  from happytransformer.args import EvalArgs, TrainArgs
  from happytransformer.fine_tuning_util import EvalResult, FistStep, ZERO_2_SETTINGS, ZERO_3_SETTINGS
label_desc: Use image node_id 15 for calling the HappyTransformer obj's underlying member method code with example usage: obj._get_eval_args(output_path, args) and returns: TrainingArguments